170 Seats
Basic Information
Course Description
Python is a general-purpose interpreted, interactive, object-oriented, and high-level programming language. Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis
What are the Python Course Pre-requisites
There are no hard pre-requisites. Basic understanding of Computer Programming terminologies is sufficient. Also, basic concepts related to Programming and Database is beeficial but not mandatory.
Objectives of the Course
- To understand the concepts and constructs of Python
- To create own Python programs, know the machine learning algorithms in Python and work on a real-time project running on Python
Who should do the course
- Big Data Professionals
- IT Developers
- Those who are showing interest to build their career in Python
Course Syllabus
- Introduction to Languages
- Introduction to Python
- Python Language Fundamentals
- Different Modes of Python
- Python Variables
- Input & Output Operators
- Control Statements
- List Collection
- Tuple Collection
- Set Collection
- Dictionary Collection
Functions
- Packages
- OOPs
- Overriding
- Overloading
- Exception Handling & Types of Errors
- Regular expressions
- File & Directory handling
- Python Logging
- Date & Time module
- Multi-threading & Multi Processing
- Garbage collection
- Python Data Base Communications(PDBC)
- Python – Network Programming
- Tkinter & Turtle
- Data analytics modules
- DJANGO
- Pandas – Introduction to Data Structures
- Pandas — Series
- Pandas – DataFrame
- Pandas – Panel
- Pandas – Basic Functionality
- Pandas – Descriptive Statistics
- Pandas – Function Application
- Pandas – Reindexing
- Pandas – Iteration
- Pandas – Sorting
- Pandas – Working with Text Data
- Pandas – Options and Customization
- Pandas – Indexing and Selecting Data
- Pandas – Statistical Functions
- Pandas – Window Functions
- Pandas – Aggregations
- Pandas – Missing Data
- Pandas – GroupBy
- Pandas – Merging/Joining
- Pandas – Concatenation
- Pandas – Categorical Data
- Pandas – Visualization
- Pandas – IO Tools
- NUMPY − DATA TYPES
- NUMPY − ARRAY ATTRIBUTES
- NUMPY − ARRAY CREATION ROUTINES
- NUMPY − ARRAY FROM EXISTING DATA
- NUMPY − ARRAY FROM NUMERICAL RANGES
- NUMPY − INDEXING & SLICING
- NUMPY − ADVANCED INDEXING
- NUMPY − ITERATING OVER ARRAY
- NUMPY – ARRAY MANIPULATION
- NUMPY – BINARY OPERATORS
- NUMPY − ARITHMETIC OPERATIONS
- NUMPY − STATISTICAL FUNCTIONS
- NUMPY − SORT, SEARCH & COUNTING FUNCTIONS
- NUMPY − BYTE SWAPPING
- NUMPY − COPIES & VIEWS
- NUMPY − MATRIX LIBRARY
- NUMPY − LINEAR ALGEBRA
- NUMPY − MATPLOTLIB
- NUMPY – HISTOGRAM USING MATPLOTLIB
- NUMPY − I/O WITH NUMPY